def find_posts_of_category_default_date(db, info_num_list, now_date,
default_date, num):
result = db[SJ_DB_POST].find(
{
'$and': [{
'info_num': {
'$in': info_num_list
}
}, {
'end_date': {
'$gt': now_date
}
}, {
'date': {
'$gt': global_func.get_default_day(default_date)
}
}]
}, {
'_id': 1,
'title': 1,
'date': 1,
'img': 1,
'fav_cnt': 1,
'view': 1,
'url': 1,
'title_token': 1,
'info': 1,
'tag': 1,
'topic': 1,
'ft_vector': 1,
'end_date': 1
}).sort([('date', -1)
]).limit(num).hint("info_num_1_end_date_-1_date_-1")
return result
def find_search_of_category_default_date(db, search_list, info_num_list,
default_date, num):
result = db[SJ_DB_POST].find(
{
'$and': [{
'token': {
'$in': search_list
}
}, {
'info_num': {
'$in': info_num_list
}
}, {
'date': {
'$gt': global_func.get_default_day(default_date)
}
}]
},
{
'_id': 1,
'title': 1,
'date': 1,
'end_date': 1,
'img': 1,
'url': 1,
'fav_cnt': 1,
'info': 1,
###############
'title_token': 1,
'token': 1,
'tag': 1,
'popularity': 1,
'ft_vector': 1
}).sort([('date', -1)]).limit(num)
return result
def find_search_log(db):
result = db[SJ_DB_SEARCH_LOG].find(
{
'date': {
'$gt': global_func.get_default_day(1)
}
}, {
'_id': 0,
'search_split': 1
}).sort([('date', -1)])
return result
def find_popularity_newsfeed(db, default_date, num):
result = db[SJ_DB_POST].find(
{
'$and': [{
'popularity': {
'$gt': 0
}
}, {
'date': {
'$gt': global_func.get_default_day(default_date)
}
}]
}, {
'_id': 1,
'title': 1,
'date': 1,
'end_date': 1,
'img': 1,
'fav_cnt': 1,
'url': 1,
'popularity': 1
}).sort([('popularity', -1)]).limit(num)
return result
def insert_dummy_post(db):
topic_temp = numpy.ones(LDA.NUM_TOPICS)
topic = (topic_temp / topic_temp.sum()).tolist()
db[SJ_DB_POST].insert({
'title':
"(o^_^)o 안녕하세요. SOOJLE 입니다.",
'date':
global_func.get_default_day(10000),
'post':
"안녕하세요. SOOJLE 입니다.",
'tag': [],
'img':
1,
'url':
"",
'hashed':
"",
'info':
"SOOJLE",
'view':
1,
'fav_cnt':
1,
'title_token': [],
'token': [],
'login':
0,
'learn':
1,
'popularity':
0,
'fav_vector': (numpy.zeros(FastText.VEC_SIZE)).tolist(),
'topic':
topic
})
return "success"
def SJ_interest_measurement_run():
db_client = MongoClient('mongodb://%s:%s@%s' %
(MONGODB_ID, MONGODB_PW, MONGODB_HOST))
db = db_client["soojle"]
renewal_time = find_variable(db, 'renewal')
USER_list = find_user_renewal(db, renewal_time)
USER_list = list(USER_list)
ACTION_DAY_CHECK = get_default_day(SJ_USER_ACTION_DAY_CHECK)
CATEGORY_list = find_all_category_of_topic(db)
CATEGORY_list = list(CATEGORY_list)
CATEGORY = {}
#뉴스피드 관심도 태그 구하기에서 빠른 접근을 위해서 dict형식으로 변환
for cate in CATEGORY_list:
CATEGORY[cate['category_name']] = cate['tag']
for USER in USER_list:
#좋아요/조회수가 하나도 없는 회원은 측정 안함.
if (len(USER['fav_list']) == 0) and (len(USER['view_list']) == 0):
continue
user_log_backup(db, USER)
fav_tag = []
view_tag = []
newsfeed_tag = []
fav_token = []
view_token = []
search_list = []
#사용자가 관심 기능을 수행한 게시물 ##########################
fav_topic = (np.zeros(LDA.NUM_TOPICS))
if len(
USER['fav_list']
) <= SJ_USER_LOG_LIMIT['fav'] * SJ_USER_ACTION_NUM_CHECK_PERCENT:
for fav in USER['fav_list']:
fav_topic += fav['topic']
fav_tag += fav['tag']
fav_token += fav['token']
else:
for fav in USER['fav_list']:
if fav['date'] < ACTION_DAY_CHECK: continue
fav_topic += fav['topic']
fav_tag += fav['tag']
fav_token += fav['token']
#FAS 구하기
fav_doc = (fav_tag + fav_token) * 2
#사용자가 접근을 수행한 게시물 ##############################
view_topic = (np.zeros(LDA.NUM_TOPICS))
if len(
USER['view_list']
) <= SJ_USER_LOG_LIMIT['view'] * SJ_USER_ACTION_NUM_CHECK_PERCENT:
for view in USER['view_list']:
view_topic += view['topic']
view_tag += view['tag']
view_token += view['token']
else:
for view in USER['view_list']:
if view['date'] < ACTION_DAY_CHECK: continue
view_topic += view['topic']
view_tag += view['tag']
view_token += view['token']
#FAS 구하기
view_doc = view_tag + view_token
#사용자가 검색을 수행한 키워드 ##############################
if len(
USER['search_list']
) <= SJ_USER_LOG_LIMIT['search'] * SJ_USER_ACTION_NUM_CHECK_PERCENT:
for search in USER['search_list']:
search_list += search['tokenizer_split']
else:
for search in USER['search_list']:
if search['date'] < ACTION_DAY_CHECK: continue
search_list += search['tokenizer_split']
search_topic = LDA.get_topics(search_list)
search_doc = search_list
#사용자가 접근한 뉴스피드 ################################
A_NUM = 0 #대학교
B_NUM = 0 #동아리&모임
C_NUM = 0 #공모전&행사
D_NUM = 0 #진로&구인
E_NUM = 0 #자유
if len(
USER['newsfeed_list']
) <= SJ_USER_LOG_LIMIT['newsfeed'] * SJ_USER_ACTION_NUM_CHECK_PERCENT:
for newsfeed in USER['newsfeed_list']:
if newsfeed['newsfeed_name'] == '대학교': A_NUM += 1
elif newsfeed['newsfeed_name'] == '동아리&모임': B_NUM += 1
elif newsfeed['newsfeed_name'] == '공모전&행사': C_NUM += 1
elif newsfeed['newsfeed_name'] == '진로&구인': D_NUM += 1
else: E_NUM += 1
else:
for newsfeed in USER['newsfeed_list']:
if newsfeed['date'] < ACTION_DAY_CHECK: continue
if newsfeed['newsfeed_name'] == '대학교': A_NUM += 1
elif newsfeed['newsfeed_name'] == '동아리&모임': B_NUM += 1
elif newsfeed['newsfeed_name'] == '공모전&행사': C_NUM += 1
elif newsfeed['newsfeed_name'] == '진로&구인': D_NUM += 1
else: E_NUM += 1
newsfeed_tag += newsfeed['tag']
newsfeed_tag += (CATEGORY['대학교'] * A_NUM) + (
CATEGORY['동아리&모임'] * B_NUM) + (CATEGORY['공모전&행사'] * C_NUM) + (
CATEGORY['진로&구인'] * D_NUM) + (CATEGORY['커뮤니티'] * E_NUM)
newsfeed_topic = LDA.get_topics(newsfeed_tag)
#가중치 작업
fav_tag *= SJ_FAV_TAG_WEIGHT
view_tag *= SJ_VIEW_TAG_WEIGHT
fav_topic *= SJ_FAV_TOPIC_WEIGHT
view_topic *= SJ_VIEW_TOPIC_WEIGHT
search_topic *= SJ_SEARCH_TOPIC_WEIGHT
newsfeed_topic *= SJ_NEWSFEED_TOPIC_WEIGHT
if len(USER['fav_list']) != 0:
fav_topic /= len(USER['fav_list'])
if len(USER['view_list']) != 0:
view_topic /= len(USER['view_list'])
#LDA Topic
TOPIC_RESULT = (fav_topic + view_topic + search_topic +
newsfeed_topic) / SJ_TOPIC_RESULT_DIV
#FASTTEXT
FastText_doc = fav_doc + view_doc + search_doc
if FastText_doc:
USER_VERCTOR = FastText.get_doc_vector(fav_doc + view_doc +
search_doc).tolist()
else:
USER_VERCTOR = ft_vector = (np.zeros(FastText.VEC_SIZE)).tolist()
#TAG
tag_dict = dict(Counter(fav_tag + view_tag))
tag_dict = sorted(tag_dict.items(), key=lambda x: x[1])
#최종 태그들 오브젝트
TAG_RESULT = {}
if len(tag_dict) >= 50:
if tag_dict[0][1] == 1:
tag_dict[0][1] = 2
TAG_RESULT[tag_dict[0][0]] = tag_dict[0][1]
for i in range(1, 50):
tag_dict[i] = list(tag_dict[i])
if (tag_dict[i - 1][1] * 1.5) < tag_dict[i][1]:
tag_dict[i][1] = int(tag_dict[i - 1][1] * 1.5)
TAG_RESULT[tag_dict[i][0]] = tag_dict[i][1]
elif len(tag_dict) > 0:
if tag_dict[0][1] == 1:
tag_dict[0][1] = 2
TAG_RESULT[tag_dict[0][0]] = tag_dict[0][1]
for i in range(1, len(tag_dict)):
tag_dict[i] = list(tag_dict[i])
if (tag_dict[i - 1][1] * 1.5) < tag_dict[i][1]:
tag_dict[i][1] = int(tag_dict[i - 1][1] * 1.5)
TAG_RESULT[tag_dict[i][0]] = tag_dict[i][1]
USER_TAG_SUM = sum(TAG_RESULT.values())
USER_TAG_SUM *= SJ_TAG_SUM_WEIGHT
if USER_TAG_SUM == 0:
USER_TAG_SUM = 1
# 사용자 태그로 사용자 태그 벡터 구하기
USER_TAGS = []
for key, value in TAG_RESULT.items():
USER_TAGS += [key] * value
TAG_VECTOR = FastText.get_doc_vector(USER_TAGS).tolist()
#해당 USER 관심도 갱신!
update_user_measurement(
db, USER['_id'], list(TOPIC_RESULT), TAG_RESULT, USER_TAG_SUM,
TAG_VECTOR, USER_VERCTOR,
len(USER['fav_list']) + len(USER['view_list']) +
len(USER['search_list']))
update_variable(db, 'renewal', datetime.now())
if db_client is not None:
db_client.close()